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          股市数据挖掘：SAS还是Clementine？
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             股市数据挖掘：SAS还是Clementine？
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               2006年12月5日 上午7:13
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              <p>
               公司要我做股市的数据挖掘，而且要求不能用别人做过的技术分析的指标。
               <br/>
               到底用哪个软件好一点阿？
               <br/>
               在一个论坛上面看到这么一个对比：
               <br/>
               1.SAS EM 在所有的数据挖掘产品中唯一一家能够将数据分为训练、验证、测试三部分并能自动地在训练数据上建模，在验证数据上进行模型调整优化，在测试数据上进行模型评估而不影响模型建立，同时还能将各种模型的提升图,ROC图等在一个 页面中显示，进而很直观地进行比较，模型哪个更好一目了然；而SPSS Clementine需要用户手动去分别创建训练、验证、测试等数据然后分别学习，相互之间无法协调，各种模型的提升图,ROC图都是分别显示的，各自为政，这样很不利于选出更好的模型和保证模型的质量。
               <br/>
               2.SAS EM的帮助文档非常全面和系统，并且还有各种数据挖掘算法的细节，而SPSS Clementine的帮助文档只涉及到软件使用上，但对各种数据挖掘算法的介绍很少，这不利于分析人员用好数据挖掘工具。
               <br/>
               3.SAS EM 能够实现并行和多线程处理，更可以利用网格计算技术提高性能，这对于处理海量数据挖掘至关重要；而SPSS Clementine 则不能。
               <br/>
               4.SAS EM 支持更广泛的输入数据格式，比如SAS EM支持EXCEL 和.dbf文件，而SPSS Clementine 不能。
               <br/>
               5.SAS EM 采用的Client/Server模式，可以充分利用服务器的处理能力，而SPSS Clementine不能。
               <br/>
               6.SAS EM可以将建好的数据挖据流程很方便地转成SAS、Java、C代码，这为模型的实施扫平了障碍，SPSS Clementine 不能。
               <br/>
               7.SAS EM可以将数据挖掘的成果很方便地发布到BI 报表系统上，而SPSS Clementine不能。
               <br/>
               8.SAS EM图形显示非常丰富，除了常见的直方图、散点图、盒须图，更有3D旋转图、等高线图；SPSS Clementine则做不到.
               <br/>
               可是他没有说：到底哪个学习的成本高一点？或者说，哪个软件比较好学好用阿？
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               2006年12月5日 下午5:44
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              <p>
               国内不知道怎么做的
               <br/>
               国外的投行和对冲基金都不用这些数据挖掘的东西，都是在unix下用C++编程，数据的话是直接从bloomberg的数据库里面下载下来
              </p>
              <p>
               有可能一些做statistical arbitrage的基金会用sas吧
              </p>
              <p>
               根据你的情况大概什么都不用，直接用excel就够了…………………………………..
              </p>
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               2006年12月6日 上午4:07
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              <p>
               excel肯定是不够用的。
               <br/>
               虽然要从一大堆数据中找出一点有用的东西很难，不过还是可以去试一试的。
               <br/>
               首先可以做一些时间序列的分析和预测，一般的统计软件里都有这个模块的。
               <br/>
               然后可以做做数据的分类。
               <br/>
               也可以试试神经网络。
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               2006年12月6日 上午8:06
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              <p>
               也许R是一个不错的选择
               <br/>
               下面有读取数据的方法
               <br/>
               R也提供了很多分析方法
               <br/>
               Jordi, I'm downloading data from Bloomberg to R sessions every day. It is relatively easy using the Bloomberg ActiveX control and the R(D)Com client package (instead of the lower-level C APIs). I don't know whether something like this is included in
               <br/>
               rMetrics. Maybe it would be useful to add it or to bundle it properly and release a specific package (if someone is interested please tell me, when I searched for it some time ago I found nothing). Here's how (to be run only from a PC with Bloomberg
               <br/>
               Workstation installed)
              </p>
              <p>
               The following code within a R session opens the connection and sets some parameters. Timeout is important as sometimes the download hangs. The other parameters are for time series:
              </p>
              <p>
               require("RDCOMClient");
               <br/>
               require("chron"); # For Date-to-ComDate transformations
              </p>
              <p>
               blCon &lt;&lt;- try(blCon &lt;- COMCreate("Bloomberg.Data.1"), silent=TRUE);
               <br/>
               if (class(blCon) == "try-error") {
               <br/>
               warning(paste("Seems like this is not a Bloomberg Workstation: ", blCon));
               <br/>
               } else {
               <br/>
               blCon[["Timeout"]] &lt;&lt;- 12000;
               <br/>
               # Constants for "DisplayNonTradingDays": Omit=0, Week=64, AllCalendar=128
               <br/>
               blCon[["DisplayNonTradingDays"]] &lt;&lt;- 64;
               <br/>
               # Constants for "NonTradingDayValue": BloombergHandles=0, PreviousDays=256, ShowNoNumber=512
               <br/>
               blCon[["NonTradingDayValue"]] &lt;&lt;- 512;
               <br/>
               # Constants for Periodicity: Daily=1, Weekly=6, Monthly=7, Annual=9
               <br/>
               blCon[["Periodicity"]] &lt;&lt;- .paOptions$frequencies[.paOptions$frequency, "BloombergPeriodicity"];
               <br/>
               }
              </p>
              <p>
               I normally  open the connection and keep it open on a global variable for subsequent downloads during the session, because closing it and opening again doesn't work straighforwardly. It seems the COM object is not really released until the garbage
               <br/>
               collector is run, and if you run the code above twice the Bloomberg connection no longer works. For a safe closing of the connection use:
              </p>
              <p>
               rm(blCon, envir=.GlobalEnv);
               <br/>
               # Explicitly invoking the garbage collector is necessary. Otherwise the COM object is not really released
               <br/>
               # and prevents any new connection to Bloomberg to be established later.
               <br/>
               gc();
              </p>
              <p>
               To download invidual indicators:
              </p>
              <p>
               blpFields &lt;- c("Long Comp Name", "Name", "Short Name", "Crncy", "Id Isin", "Ticker", "Exch Code", "Market Sector Des");
               <br/>
               blpTicker &lt;- "TEF SM Equity";
              </p>
              <p>
               figures &lt;- try(blCon$BlpSubscribe(Security=blpTicker, Fields=blpFields));
              </p>
              <p>
               if (class(figures) != "try-error") {
               <br/>
               blCon$Desubscribe(ids);       # Just in case…
              </p>
              <p>
               # Enable access to fields by name. Spaces are substituted by dots.
               <br/>
               names(figures) &lt;- make.names(blpFields);
              </p>
              <p>
               # Flatten the list for easier access (figures["Short Name"] instead of figures["Short Name"][[1]])
               <br/>
               figures &lt;- unlist(figures, recursive=FALSE);
              </p>
              <p>
               # Turn Bloomberg codes such as '#N/A N Ap' to NAs
               <br/>
               figures &lt;- lapply(figures, FUN=function(x) {  if (x %in% c("#N/A N Ap", "#N/A N.A.")) NA else x; })
              </p>
              <p>
               # Check the ticker has been found
               <br/>
               if (figures[1] == "#N/A Sec")
               <br/>
               stop(paste("Bloomberg ticker", sQuote(blpTicker), "not found"));
               <br/>
               }
              </p>
              <p>
               Then you can access the downloaded data with figures$Name, figures$Market.Sector.Des, etc.
              </p>
              <p>
               To download time series, you first need to specify the date range. I use the R 1.9.0 new Date object, which needs to be transformed to COMDate objects, for what I use the following functions adapted from R(D)Com client examples (using POSIXlt instead of
               <br/>
               Date requires trivial changes, I used it before R 1.9.0 was released):
              </p>
              <p>
               # FUNCTION: as.Date.comDate
               <br/>
               # DESCRIPTION: Transform a Date object to a COMDate object
               <br/>
               # NOTE: Adapted from RCOM client code examples
               <br/>
               as.Date.comDate &lt;- function(comDate, date1904 = FALSE) {
               <br/>
               if(date1904){
               <br/>
               orig &lt;- c(month=12, day=31, year=1903);
               <br/>
               off &lt;- 0;
               <br/>
               }
               <br/>
               else {
               <br/>
               orig &lt;- c(month=12, day=31, year=1899);
               <br/>
               off &lt;- 1;
               <br/>
               }
              </p>
              <p>
               as.Date(chron(as.numeric(comDate) – off, origin = c(month=12, day=31, year=1899)));
               <br/>
               }
              </p>
              <p>
               # FUNCTION: as.comDate.Date
               <br/>
               # DESCRIPTION: Tranforms a COMDate object to a Date object
               <br/>
               # NOTE: Adapted from RCOM client code examples
               <br/>
               as.comDate.Date &lt;- function(aDate, date1904 = FALSE)
               <br/>
               {
               <br/>
               chronDate &lt;- chron(unclass(aDate));
               <br/>
               if (date1904){
               <br/>
               orig &lt;- c(month=12, day=31, year=1903);
               <br/>
               off &lt;- 0;
               <br/>
               }
               <br/>
               else {
               <br/>
               orig &lt;- c(month=12, day=31, year=1899);
               <br/>
               off &lt;- 1;
               <br/>
               }
              </p>
              <p>
               if(any(origin(chronDate)!=orig))
               <br/>
               origin(chronDate) &lt;- orig;
              </p>
              <p>
               result &lt;- new("COMDate");
               <br/>
               result[1] &lt;- round(as.numeric(chronDate) + off);
              </p>
              <p>
               result;
               <br/>
               }
              </p>
              <p>
               And then, to download time series into an R matrix:
              </p>
              <p>
               # Turn dates to COMDate's
               <br/>
               from &lt;- as.Date("2000-12-31");
               <br/>
               to &lt;- Sys.Date()-1;     # Yesterday
               <br/>
               comFrom &lt;-  as.comDate.Date(from);
               <br/>
               comTo &lt;- as.comDate.Date(to);
               <br/>
               blpTicker &lt;- "TEF SM Equity";
              </p>
              <p>
               histData &lt;- try(blCon$BLPGetHistoricalData(Security=blpTicker, Fields="PX_LAST",
               <br/>
               StartDate=comFrom, EndDate=comTo));
               <br/>
               if (class(histData) != "try-error") {
               <br/>
               # Check the ticker has been found
               <br/>
               if (histData[[2]][[1]][1] == "#N/A History") {
               <br/>
               warning(paste("History not available for Bloomberg ticker", blpTicker, "between", from, "and", to));
               <br/>
               } else {
               <br/>
               # Transform Bloomberg result to a R matrix whose row names are strings with the dates
               <br/>
               price &lt;- matrix(as.numeric(histData[[2]][[1]]), nrow=length(histData[[2]][[1]]), ncol=1,
               <br/>
               dimnames=list(format(as.Date.comDate(histData[[1]][[1]]), "d/M/yyyy"), code));
               <br/>
               }
               <br/>
               }
              </p>
              <p>
               Then you can move your data in R objects to a database using the RODBC package. This has be adapted to your particular database schema.
              </p>
              <p>
               Hope this helps.
              </p>
              <p>
               Enrique
               <br/>
               ___________________________________________________________________________
              </p>
              <p>
               Enrique Bengoechea
               <br/>
               Investment Consulting – CREDIT SUISSE Spain
              </p>
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            <div class="bbp-reply-header" id="post-214462">
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              <span class="bbp-reply-post-date">
               2006年12月6日 上午8:07
              </span>
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               abel
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              <p>
               RMetrics系列中也提供了读取现有宏观经济数据的内置方法，可以参考一下。
              </p>
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            <div class="bbp-reply-header" id="post-219471">
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              <span class="bbp-reply-post-date">
               2007年3月2日 上午10:01
              </span>
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               6 楼
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               lisi
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              <p>
               果然是R的忠实Fans
              </p>
             </div>
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            <div class="bbp-reply-header" id="post-219821">
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              <span class="bbp-reply-post-date">
               2007年3月9日 下午2:56
              </span>
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               7 楼
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              <a class="bbp-author-name" href="http://cos.name/cn/profile/1/" rel="nofollow" title="查看谢益辉的档案">
               谢益辉
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               站长
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              <p>
               你也来了啊：）
              </p>
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            <div class="bbp-reply-header" id="post-222649">
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              <span class="bbp-reply-post-date">
               2007年4月12日 上午2:46
              </span>
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               8 楼
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               33859007
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             <div class="bbp-reply-content">
              <p>
               对于自己而言很多软件都有利弊,就要综合考虑,费用\熟悉程度\解决方案….等等
              </p>
             </div>
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            <div class="bbp-reply-header" id="post-225121">
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              <span class="bbp-reply-post-date">
               2007年5月11日 上午9:25
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             <div class="bbp-reply-content">
              <p>
               数据挖掘网上评论是SAS最好用，我就在找那软件
              </p>
             </div>
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            <div class="bbp-reply-header" id="post-225824">
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              <span class="bbp-reply-post-date">
               2007年5月20日 上午4:07
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             <div class="bbp-reply-content">
              <p>
               1.SAS EM 在所有的数据挖掘产品中唯一一家能够将数据分为训练、验证、测试三部分并能自动地在训练数据上建模，在验证数据上进行模型调整优化，在测试数据上进行模型评估而不影响模型建立，同时还能将各种模型的提升图,ROC图等在一个 页面中显示，进而很直观地进行比较，模型哪个更好一目了然；而SPSS Clementine需要用户手动去分别创建训练、验证、测试等数据然后分别学习，相互之间无法协调，各种模型的提升图,ROC图都是分别显示的，各自为政，这样很不利于选出更好的模型和保证模型的质量。
              </p>
              <p>
               这个区别是有，但是CLE后续版本有改进
              </p>
              <p>
               2.SAS EM的帮助文档非常全面和系统，并且还有各种数据挖掘算法的细节，而SPSS Clementine的帮助文档只涉及到软件使用上，但对各种数据挖掘算法的介绍很少，这不利于分析人员用好数据挖掘工具。
               <br/>
               呵呵，一般的用户你还要自己做算法啊？CLE可以自己写算法，然后可以调用其他的如ORACLE,IBM的算法
              </p>
              <p>
               3.SAS EM 能够实现并行和多线程处理，更可以利用网格计算技术提高性能，这对于处理海量数据挖掘至关重要；而SPSS Clementine 则不能。
               <br/>
               现在的版本好像支持
               <br/>
               4.SAS EM 支持更广泛的输入数据格式，比如SAS EM支持EXCEL 和.dbf文件，而SPSS Clementine 不能。
               <br/>
               CLE 10.0开始支持EXCEL了，再说了，这个无所谓。你要是都一EXCEL文件，还用挖掘么？就那么点样本量，
              </p>
              <p>
               5.SAS EM 采用的Client/Server模式，可以充分利用服务器的处理能力，而SPSS Clementine不能。
               <br/>
               CLE早就可以了，但是你自己用，你又没服务器
              </p>
              <p>
               6.SAS EM可以将建好的数据挖据流程很方便地转成SAS、Java、C代码，这为模型的实施扫平了障碍，SPSS Clementine 不能。
               <br/>
               PMMI功能可以实现共享
              </p>
              <p>
               7.SAS EM可以将数据挖掘的成果很方便地发布到BI 报表系统上，而SPSS Clementine不能。
               <br/>
               这个不太清楚
              </p>
              <p>
               8.SAS EM图形显示非常丰富，除了常见的直方图、散点图、盒须图，更有3D旋转图、等高线图；SPSS Clementine则做不到.
               <br/>
               CLE10.1的插件里面有
               <br/>
               可是他没有说：到底哪个学习的成本高一点？或者说，哪个软件比较好学好用阿？
               <br/>
               CLE容易用得多，SAS好没问题，但是很多人一提CLE，SPSS的软件就很鄙夷。要知道很多电信公司用，我的那本台湾教材，日本NIKON公司也用。
               <br/>
               我一直觉得应该把精力放在商业理解和行业经验上，软件的差异对结果影响甚小，不是说你用SAS就如何，这个挖掘成功与否不取决与软件，希望大家不要把过多的精力放在追逐软件上面。
               <br/>
               希望大家拍砖
              </p>
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            <div class="bbp-reply-header" id="post-228555">
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              <span class="bbp-reply-post-date">
               2007年7月4日 上午9:29
              </span>
              <a class="bbp-reply-permalink" href="http://cos.name/cn/topic/2822/#post-228555">
               11 楼
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             <div class="bbp-reply-content">
              <p>
               同意楼上的！
               <br/>
               把精力放在实质性的东西上面。
              </p>
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            <div class="bbp-reply-header" id="post-228700">
             <div class="bbp-meta">
              <span class="bbp-reply-post-date">
               2007年7月8日 上午9:10
              </span>
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               12 楼
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              <p>
               神经网络有专门的软件直接做证券的
              </p>
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            <div class="bbp-reply-header" id="post-228955">
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              <span class="bbp-reply-post-date">
               2007年7月15日 下午2:50
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               13 楼
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              <p>
               短期的应用用SPSS就行了~~
               <br/>
               不过要是你时间充裕那还是坐下来花个一两个月学学SAS吧~~
              </p>
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            <div class="bbp-reply-header" id="post-229444">
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              <span class="bbp-reply-post-date">
               2007年7月23日 下午3:53
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               14 楼
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              <p>
               SAS也罢,SPSS也罢,如果你们要买软件的话,SPSS性价比高点,如果你们用盗版,可以两个都试试!不过如果你想了解Clementine,可以联系我了,邮箱&amp;MSN:bili_zhou@hotmail.com
              </p>
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            <div class="bbp-reply-header" id="post-251036">
             <div class="bbp-meta">
              <span class="bbp-reply-post-date">
               2008年6月13日 上午2:58
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               15 楼
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               我以前 做过 股票的数据挖掘 就是用 matlab写的
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               其实用什么都无所谓的
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